Color features provide the information about color distribution in an image. Since psoriasis images are color images, color features provide valuable information to discriminate psoriatic lesion and healthy skin. Two statistics, i.e., mean and standard deviation for each color component of four color spaces SB431542 calculated (Celebi et al., 2007). The mean value characterizes the average color and standard deviation represents the color variation corresponding to color component considered. The color spaces considered are RGB, HSV, YCbCr and CIE L∗a∗b∗. RGB is the red–green–blue color space, HSV represent hue, saturation and value color space, YCbCr represents luminance and chrominance color space and CIE L∗a∗b∗ represents lightness and color-component space. Since each color space contains three color components, a total of 24 color features (4 color spaces × 3 color components × 2 statistics) are extracted for each sample image as shown in Table 1. After color space conversions i.e., RGB to HSV, RGB to CIE L∗a∗b∗ (Gonzalez & Woods, 2002, chap. 6) and RGB to YCbCr (Ahirwal, Khadtare, & Mehta, 2007), the mean and standard deviation are calculated for each color component of each color space using following equations:equation(18)μIo=1(rw∗cl)∑i=1rw∑j=1clIo(i,j)equation(19)σIo=1(rw∗cl)∑i=1rw∑j=1clIoi,j-μIo2where, Io(i,j)Io(i,j) is eyespot the value of particular color component in the iith row and jjth column. rw×clrw×cl is the size of the sample image. μIoμIo and σIoσIo represent the mean and standard deviation of corresponding color component for sample image considered.